Author(s)

Pengjiao Liu, Gongliu Yang, Suier Wang

Corresponding Author

Pengjiao Liu

ABSTRACT

For the nonlinear, non-stationary and weak correlation signals existing in a MEMS (Microelectronic-mechanic system) gyro, a denosing method based on improved Adaptive Time-scale Decomposition (IATD) was proposed. The signals, which was captured by the static experiment, were decomposed into a cluster of intrinsic time-scale component based on IADT process. Then, according to the characteristics of the gyro random error, the gyro signals were reconstructed to implement the signal denoising. AR (2) model was applied to set up a mathematical model of the reconstructed signals. After filtering and modeling, the random error of gyro is reduced by 83.72%, which means the random error of MEMS gyro is suppressed effectively.

KEYWORDS

Adaptive Time-Scale Decomposition, Mems Gyro, Ar Model, Random Error